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Related papers: On consistent estimation of dimension values

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The concept of angle, angle functions, and the question how to measure angles present old and well-established mathematical topics referring to Euclidean space, and there exist also various extensions to non-Euclidean spaces of different…

Metric Geometry · Mathematics 2016-07-26 Vitor Balestro , Ákos G. Horváth , Horst Martini , Ralph Teixeira

We discuss various infinite-dimensional configuration spaces that carry measures quasiinvariant under compactly-supported diffeomorphisms of a manifold M corresponding to a physical space. Such measures allow the construction of unitary…

Mathematical Physics · Physics 2009-11-10 Gerald A. Goldin , Ugo Moschella , Takao Sakuraba

A finite set of unlabelled points in Euclidean space is the simplest representation of many real objects from mineral rocks to sculptures. Since most solid objects are rigid, their natural equivalence is rigid motion or isometry maintaining…

Metric Geometry · Mathematics 2023-03-27 Vitaliy Kurlin

A solution manifold is the collection of points in a $d$-dimensional space satisfying a system of $s$ equations with $s<d$. Solution manifolds occur in several statistical problems including hypothesis testing, curved-exponential families,…

Statistics Theory · Mathematics 2021-12-15 Yen-Chi Chen

We consider density estimators based on the nearest neighbors method applied to discrete point distibutions in spaces of arbitrary dimensionality. If the density is constant, the volume of a hypersphere centered at a random location is…

Instrumentation and Methods for Astrophysics · Physics 2013-01-24 Przemek Wozniak , Andrzej Kruszewski

Polyhedral-type approximations of convex-like domains in $\mathbb{C}^d$ have been considered recently by the second author. In particular, the decay rate of the error in optimal volume approximation as a function of the number of facets has…

Probability · Mathematics 2022-03-24 Siva Athreya , Purvi Gupta , D. Yogeshwaran

The Johnson-Lindenstrauss transform is a fundamental method for dimension reduction in Euclidean spaces, that can map any dataset of $n$ points into dimension $O(\log n)$ with low distortion of their distances. This dimension bound is tight…

Data Structures and Algorithms · Computer Science 2026-02-20 Shaofeng H. -C. Jiang , Robert Krauthgamer , Shay Sapir , Sandeep Silwal , Di Yue

The concepts of spread and spread dimension of a metric space were introduced by Willerton in the context of quantifying biodiversity of ecosystems. In previous work, we developed the theoretical basis for applications of spread dimension…

Metric Geometry · Mathematics 2024-08-28 Kevin Dunne

This paper describes an approach that uses flat-spacetime dimension estimators to estimate the manifold dimension of causal sets that can be faithfully embedded into curved spacetimes. The approach is invariant under coarse graining and can…

General Relativity and Quantum Cosmology · Physics 2009-11-07 David D. Reid

Let $n>m$, and let $A$ be an $(m\times n)$-matrix of full rank. Then obviously the estimate $\|Ax\|\leq\|A\|\|x\|$ holds for the euclidean norm of $x$ and $Ax$ and the spectral norm as the assigned matrix norm. We study the sets of all $x$…

Rings and Algebras · Mathematics 2022-03-16 Harry Yserentant

In this paper, we study the smoothness of the density function of absolutely continuous measures supported on random self-similar sets on the line. We show that the natural projection of a measure with symbolic local dimension greater than…

Dynamical Systems · Mathematics 2025-05-20 Balázs Bárány , Michał Rams

We propose a new method for estimating the intrinsic dimension of a dataset by applying the principle of regularized maximum likelihood to the distances between close neighbors. We propose a regularization scheme which is motivated by…

Machine Learning · Computer Science 2012-03-19 Mithun Das Gupta , Thomas S. Huang

Let ${\bf K} = (K_1, ..., K_n)$ be an $n$-tuple of convex compact subsets in the Euclidean space $\R^n$, and let $V(\cdot)$ be the Euclidean volume in $\R^n$. The Minkowski polynomial $V_{{\bf K}}$ is defined as $V_{{\bf K}}(\lambda_1, ...…

Computational Geometry · Computer Science 2009-01-19 Leonid Gurvits

This article provides an overview on the statistical modeling of complex data as increasingly encountered in modern data analysis. It is argued that such data can often be described as elements of a metric space that satisfies certain…

Methodology · Statistics 2024-02-28 Paromita Dubey , Yaqing Chen , Hans-Georg Müller

Statistical depths provide a fundamental generalization of quantiles and medians to data in higher dimensions. This paper proposes a new type of globally defined statistical depth, based upon control theory and eikonal equations, which…

Statistics Theory · Mathematics 2022-01-17 Martin Molina-Fructuoso , Ryan Murray

We study the geometric significance of Leinster's notion of magnitude for a smooth manifold with boundary of arbitrary dimension, motivated by open questions for the unit disk in $\mathbb{R}^2$. For a large class of distance functions,…

Differential Geometry · Mathematics 2025-11-18 Heiko Gimperlein , Magnus Goffeng , Nikoletta Louca

We prove several inequalities estimating the distance between volumes of two bodies in terms of the maximal or minimal difference between areas of sections or projections of these bodies. We also provide extensions in which volume is…

Metric Geometry · Mathematics 2016-08-12 Apostolos Giannopoulos , Alexander Koldobsky

We investigate the interplay and connections between symmetry properties of equations, the interpretation of coordinates, the construction of observables, and the existence of physical relativity principles in spacetime theories. Using the…

General Relativity and Quantum Cosmology · Physics 2009-06-30 Hans Westman , Sebastiano Sonego

The multiverse/landscape paradigm that has emerged from eternal inflation and string theory, describes a large-scale multiverse populated by "pocket universes" which come in a huge variety of different types, including different…

High Energy Physics - Theory · Physics 2014-11-20 Delia Schwartz-Perlov , Alexander Vilenkin

We consider a randomly forced Ginzburg-Landau equation on an unbounded domain. The forcing is smooth and homogeneous in space and white noise in time. We prove existence and smoothness of solutions, existence of an invariant measure for the…

Analysis of PDEs · Mathematics 2007-05-23 Jacques Rougemont
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